目的观察围手术期电针干预髋关节置换术后患者谵妄(POD)的临床疗效。方法将128例行髋关节置换术的患者随机分为治疗组和对照组,每组64例。治疗组在围手术期采用电针治疗,对照组进行常规术前准备及术后治疗。观察两组患者术前1 d、手术...目的观察围手术期电针干预髋关节置换术后患者谵妄(POD)的临床疗效。方法将128例行髋关节置换术的患者随机分为治疗组和对照组,每组64例。治疗组在围手术期采用电针治疗,对照组进行常规术前准备及术后治疗。观察两组患者术前1 d、手术结束时及术后1 d血清星形胶质源性蛋白(S100β)的浓度变化,并比较两组术后3 d POD的发生率。结果两组术后1 d POD发生率与同组出恢复室时比较,差异均具有统计学意义(P<0.01)。治疗组术后2、3 d POD发生率明显低于同组术后1 d(均P<0.05),治疗组术后3 d POD发生率明显低于同组术后2 d(P<0.05)。治疗组不同时间点(出恢复室及术后1~3 d)POD发生率与对照组比较,差异均具有统计学意义(P<0.01)。两组手术结束时及术后1 d S100β浓度与同组术前比较,差异均具有统计学意义(P<0.05)。治疗组术后1 d S100β浓度与同组手术结束时比较,差异具有统计学意义(P<0.05)。治疗组手术结束时及术后1 d S100β浓度与对照组比较,差异均具有统计学意义(P<0.05)。结论围手术期电针治疗能有效降低髋关节置换术后患者谵妄的发生率,并减少其持续时间。展开更多
The linear behavior of the dominant unstable mode(m=2,n=1)and its high order harmonics(m=2n,n≥2)are numerically investigated in a reversed magnetic shear cylindrical plasma with two q=2 rational surfaces on the basis...The linear behavior of the dominant unstable mode(m=2,n=1)and its high order harmonics(m=2n,n≥2)are numerically investigated in a reversed magnetic shear cylindrical plasma with two q=2 rational surfaces on the basis of the non-reduced magnetohydrodynamics(MHD)equations.The results show that with low beta(beta is defined as the ratio of plasma pressure to magnetic field pressure),the dominant mode is a classical double tearing mode(DTM).However,when the beta is sufficiently large,the mode is driven mainly by plasma pressure.In such a case,both the linear growth rate and mode structures are strongly affected by pressure,while almost independent of the resistivity.This means that the dominant mode undergoes a transition from DTM to pressure-driven mode with the increase of pressure,which is consistent with the experimental result in ASDEX Upgrade.The simulations also show that the distance between two rational surfaces has an important influence on the pressure needed in mode transition.The larger the distance between two rational surfaces,the larger the pressure for driving the mode transition is.Motivated by the phenomena that the high-m modes may dominate over low-m modes at small inter-resonance distance,the high-m modes with different pressures and q profiles are studied too.展开更多
Multiagent deep reinforcement learning (MA-DRL) has received increasingly wide attention. Most of the existing MA-DRL algorithms, however, are still inefficient when faced with the non-stationarity due to agents chang...Multiagent deep reinforcement learning (MA-DRL) has received increasingly wide attention. Most of the existing MA-DRL algorithms, however, are still inefficient when faced with the non-stationarity due to agents changing behavior consistently in stochastic environments. This paper extends the weighted double estimator to multiagent domains and proposes an MA-DRL framework, named Weighted Double Deep Q-Network (WDDQN). By leveraging the weighted double estimator and the deep neural network, WDDQN can not only reduce the bias effectively but also handle scenarios with raw visual inputs. To achieve efficient cooperation in multiagent domains, we introduce a lenient reward network and scheduled replay strategy. Empirical results show that WDDQN outperforms an existing DRL algorithm (double DQN) and an MA-DRL algorithm (lenient Q-learning) regarding the averaged reward and the convergence speed and is more likely to converge to the Pareto-optimal Nash equilibrium in stochastic cooperative environments.展开更多
To the Editor： According to the Chinese National Bureau of Statistics in October 1999, the population aged ≥60 years reached 10% of the total population, indicating that China was entering into an aging society, By ...To the Editor： According to the Chinese National Bureau of Statistics in October 1999, the population aged ≥60 years reached 10% of the total population, indicating that China was entering into an aging society, By the end of 2017, the population aged ≥60 years was 240,900,000, accounting for 17.3% of the total population. With the rapidly aging population, binary diseases in elderly patients have become frequent in China, with a morbidity rate of 8-11%. Due to lowered stress response, defense ability, and immunity, biliary diseases in elderly patients are characterized by an increase in coexisting diseases, rapid progression, poor surgical tolerance, high surgical risk, frequent postoperative complications, and high mortality. Thus, it is important to explore effective treatment methods in elderly patients with biliary diseases. Based on our clinical experience in the treatment of elderly patients with biliary diseases,[1] along with previous studies, this report presented the current status of surgical treatment of elderly patients with biliary diseases in China.[2]展开更多
文摘目的观察围手术期电针干预髋关节置换术后患者谵妄(POD)的临床疗效。方法将128例行髋关节置换术的患者随机分为治疗组和对照组,每组64例。治疗组在围手术期采用电针治疗,对照组进行常规术前准备及术后治疗。观察两组患者术前1 d、手术结束时及术后1 d血清星形胶质源性蛋白(S100β)的浓度变化,并比较两组术后3 d POD的发生率。结果两组术后1 d POD发生率与同组出恢复室时比较,差异均具有统计学意义(P<0.01)。治疗组术后2、3 d POD发生率明显低于同组术后1 d(均P<0.05),治疗组术后3 d POD发生率明显低于同组术后2 d(P<0.05)。治疗组不同时间点(出恢复室及术后1~3 d)POD发生率与对照组比较,差异均具有统计学意义(P<0.01)。两组手术结束时及术后1 d S100β浓度与同组术前比较,差异均具有统计学意义(P<0.05)。治疗组术后1 d S100β浓度与同组手术结束时比较,差异具有统计学意义(P<0.05)。治疗组手术结束时及术后1 d S100β浓度与对照组比较,差异均具有统计学意义(P<0.05)。结论围手术期电针治疗能有效降低髋关节置换术后患者谵妄的发生率,并减少其持续时间。
基金Project supported by the Research Foundation of Education Bureau of Hunan Province,China (Grant No.21B0648)the National Natural Science Foundation of China (Grant Nos.11805239,12075282,and 11775268)the Natural Science Foundation of Hunan Province,China (Grant No.2019JJ50011)。
文摘The linear behavior of the dominant unstable mode(m=2,n=1)and its high order harmonics(m=2n,n≥2)are numerically investigated in a reversed magnetic shear cylindrical plasma with two q=2 rational surfaces on the basis of the non-reduced magnetohydrodynamics(MHD)equations.The results show that with low beta(beta is defined as the ratio of plasma pressure to magnetic field pressure),the dominant mode is a classical double tearing mode(DTM).However,when the beta is sufficiently large,the mode is driven mainly by plasma pressure.In such a case,both the linear growth rate and mode structures are strongly affected by pressure,while almost independent of the resistivity.This means that the dominant mode undergoes a transition from DTM to pressure-driven mode with the increase of pressure,which is consistent with the experimental result in ASDEX Upgrade.The simulations also show that the distance between two rational surfaces has an important influence on the pressure needed in mode transition.The larger the distance between two rational surfaces,the larger the pressure for driving the mode transition is.Motivated by the phenomena that the high-m modes may dominate over low-m modes at small inter-resonance distance,the high-m modes with different pressures and q profiles are studied too.
基金The work was supported by the National Natural Science Foundation of China under Grant Nos.61702362,U1836214,and 61876119the Special Program of Artificial Intelligence of Tianjin Research Program of Application Foundation and Advanced Technology under Grant No.16JCQNJC00100+3 种基金the Special Program of Artificial Intelligence of Tianjin Municipal Science and Technology Commission of China under Grant No.56917ZXRGGX00150the Science and Technology Program of Tianjin of China under Grant Nos.15PTCYSY00030 and 16ZXHLGX00170the Natural Science Foundation of Jiangsu Province of China under Grant No.BK20181432Acknowledgments We thank our industrial re search partner Netease, Inc., especially the Fuxi AILaboratory of Leihuo Business Groups for their discus sion and support with the experiments.
文摘Multiagent deep reinforcement learning (MA-DRL) has received increasingly wide attention. Most of the existing MA-DRL algorithms, however, are still inefficient when faced with the non-stationarity due to agents changing behavior consistently in stochastic environments. This paper extends the weighted double estimator to multiagent domains and proposes an MA-DRL framework, named Weighted Double Deep Q-Network (WDDQN). By leveraging the weighted double estimator and the deep neural network, WDDQN can not only reduce the bias effectively but also handle scenarios with raw visual inputs. To achieve efficient cooperation in multiagent domains, we introduce a lenient reward network and scheduled replay strategy. Empirical results show that WDDQN outperforms an existing DRL algorithm (double DQN) and an MA-DRL algorithm (lenient Q-learning) regarding the averaged reward and the convergence speed and is more likely to converge to the Pareto-optimal Nash equilibrium in stochastic cooperative environments.
文摘To the Editor： According to the Chinese National Bureau of Statistics in October 1999, the population aged ≥60 years reached 10% of the total population, indicating that China was entering into an aging society, By the end of 2017, the population aged ≥60 years was 240,900,000, accounting for 17.3% of the total population. With the rapidly aging population, binary diseases in elderly patients have become frequent in China, with a morbidity rate of 8-11%. Due to lowered stress response, defense ability, and immunity, biliary diseases in elderly patients are characterized by an increase in coexisting diseases, rapid progression, poor surgical tolerance, high surgical risk, frequent postoperative complications, and high mortality. Thus, it is important to explore effective treatment methods in elderly patients with biliary diseases. Based on our clinical experience in the treatment of elderly patients with biliary diseases,[1] along with previous studies, this report presented the current status of surgical treatment of elderly patients with biliary diseases in China.[2]
